"A server or tool using RAG for documentation scraping, storage, and retrieval with SSE support" matching MCP tools:

• fetch

  OneQAZ Trading Intelligence

  Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: id: document id — "tool:{name}", "resource:{uri}", or "signal:{market}:{symbol}" (market: crypto / kr_stock / us_stock) Disclaimer: Information only, not investment advice.

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• save_palette

  rnv-color-mcp

  Persist a named color palette for later retrieval with get_palette or list_palettes. colors is a list of hex values; optional notes are stored as the palette's description. Author is recorded as RNVizion. This WRITES to the palette store and is the only tool here that does. Reusing an existing name overwrites that palette: save and update are the same call (an upsert), there is no separate update operation. Returns a `durable` flag: true if the palette reached durable storage (the HF Dataset) and will survive a restart, false if it saved to the local working copy only (which is lost on rebuild, e.g. when the Space HF_TOKEN is missing or lacks write scope). Use when the user wants to keep a set of colors under a name for reuse across sessions, such as a brand or launch palette; to read a palette back use get_palette, and to see what already exists use list_palettes. The saved name can then be passed to mix_colors, convert_color, and generate_harmony as a palette reference.

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• microsoft_docs_fetch

  Microsoft Learn MCP

  Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.

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• stream_task

  TunnelMind Data API

  Opens a persistent SSE connection that emits events as the task progresses. The stream closes automatically when the task reaches a terminal state or after ~90 seconds (timeout). Heartbeat comments are sent every ~15 seconds to keep the connection alive through proxies. Event types: - `status` — emitted when status changes (pending → running → complete/failed) - `result` — emitted on `complete` with the full result payload - `error` — emitted on `failed`, `cancelled`, or `expired` with error info - SSE comment (`: heartbeat`) — keepalive, no data Use this tool when: - You want real-time progress without polling. - You are in an environment that supports SSE (EventSource API). Do NOT use this tool when: - You want a simple one-shot status check — use `get_task` instead. - Your HTTP client doesn't support streaming responses. Inputs: - `task_id` (path, required): 26-char ULID. Returns: - SSE stream (`text/event-stream`). Each event is `event: <type>\\ndata: <json>\\n\\n`. Cost: - Free. Counts as one request against rate limits when the stream opens. Latency: - First event: <200ms. Stream duration: up to 90s.

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• import_data

  mcp

  Import data into a Cloud SQL instance. If the file doesn't start with `gs://`, then the assumption is that the file is stored locally. If the file is local, then the file must be uploaded to Cloud Storage before you can make the actual `import_data` call. To upload the file to Cloud Storage, you can use the `gcloud` or `gsutil` commands. Before you upload the file to Cloud Storage, consider whether you want to use an existing bucket or create a new bucket in the provided project. After the file is uploaded to Cloud Storage, the instance service account must have sufficient permissions to read the uploaded file from the Cloud Storage bucket. This can be accomplished as follows: 1. Use the `get_instance` tool to get the email address of the instance service account. From the output of the tool, get the value of the `serviceAccountEmailAddress` field. 2. Grant the instance service account the `storage.objectAdmin` role on the provided Cloud Storage bucket. Use a command like `gcloud storage buckets add-iam-policy-binding` or a request to the Cloud Storage API. It can take from two to up to seven minutes or more for the role to be granted and the permissions to be propagated to the service account in Cloud Storage. If you encounter a permissions error after updatingthe IAM policy, then wait a few minutes and try again. After permissions are granted, you can import the data. We recommend that you leave optional parameters empty and use the system defaults. The file type can typically be determined by the file extension. For example, if the file is a SQL file, `.sql` or `.csv` for CSV file. The following is a sample SQL `importContext` for MySQL. ``` { "uri": "gs://sample-gcs-bucket/sample-file.sql", "kind": "sql#importContext", "fileType": "SQL" } ``` There is no `database` parameter present for MySQL since the database name is expected to be present in the SQL file. Specify only one URI. No other fields are required outside of `importContext`. For PostgreSQL, the `database` field is required. The following is a sample PostgreSQL `importContext` with the `database` field specified. ``` { "uri": "gs://sample-gcs-bucket/sample-file.sql", "kind": "sql#importContext", "fileType": "SQL", "database": "sample-db" } ``` The `import_data` tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes.

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• collection.ask

  DocImprint

  Answer a question using RAG over a document collection. Retrieves relevant chunks then synthesizes a cited answer with source attribution. Use when you need a direct answer grounded in your collection documents. For raw matching chunks (without synthesis), use collection.search instead. For single-document Q&A, use url.qa instead. PREREQUISITE: Collection must be populated via collection.add_document and indexed before results appear. Returns: { answer: string, sources: [{ bundle_id, chunk_id }], retrieval: [{ bundle_id, chunk_id, text, score }] } Example prompts: - "What are the key terms of the service agreement in my collection?" - "Based on my due diligence docs, what are the main risks?" - "Answer this question using all documents in the Q4 Contracts collection."

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• semantic_search

  canton-ccpedia

  PRIMARY tool for open-ended questions: how / why / what-is, troubleshooting a symptom ("why is my balance zero", "how do I fix X"), and locating config or setup steps. Conceptual/meaning-based search over the full Canton corpus (CIPs, docs, forum, mailing lists, proposals, blog, releases, ecosystem, foundation KB, YouTube) using vector+FTS hybrid retrieval with reranking. Canton-specific. Use this FIRST for anything a specific tool does not clearly own; the narrow curated tools (get_faq, find_known_issues, diagnose_error) cover only small hand-picked sets or need a literal error string, so prefer semantic_search for real how/why/config questions. Then call get_doc with a returned id to read the full source page.

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• search_documentation

  JobMojito

  Search ALL JobMojito documentation. This is the single entry point. One call searches both documentation sources in parallel and returns a merged, source-labeled list — you do not need to choose a source or call a separate tool: • "developer" — developer.jobmojito.com: API reference, request/response schemas, tables, webhooks, code examples, integration guides. • "help" — help.jobmojito.com: recruiter, candidate, and administrator product guides (how the platform behaves for end users). Use this whenever you need to understand how a feature, endpoint, field, or workflow works — including before calling an action tool you're unsure about. Then call `get_documentation(url)` with a returned URL to read the full page.

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• purchase_enterprise_license

  Opedd — Licensed Content for AI

  Purchase a bulk enterprise license covering multiple publishers (Phase 10). Returns a Stripe client_secret for payment completion + the enterprise_license_id. After payment, an ent_* access key is emailed to buyer_email. Scopes: 'custom' (pass-through publisher_ids), 'platform_wide' (auto-resolve all opted-in publishers), 'filtered' (Phase 10 filter_rules). License tiers: 'rag' (= ai_retrieval), 'training' (= ai_training, flat-fee not metered), 'inference' (= ai_retrieval), 'full_ai' (writes both retrieval + training records). The buyer must accept the Opedd Master Services Agreement (opedd.com/terms) before purchase — set terms_accepted=true to record it.

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• tflogs

  InsideOut (Riley)

  MONITORING: Fetch Terraform deployment logs with pagination Fetches logs from a running or completed Terraform deployment job. For **completed jobs**: uses REST endpoint for instant retrieval (supports `tail` for server-side filtering). For **running jobs**: streams via SSE with timeout-based pagination. **PAGINATION** (running jobs only): Use `last_event_id` from the response to fetch more: 1. First call: `tflogs(session_id='...')` → get logs + `last_event_id` 2. Next call: `tflogs(session_id='...', last_event_id='...')` → get NEW logs only 3. Repeat until `complete: true` in response **RESPONSE FIELDS**: - `logs`: Array of log messages collected - `last_event_id`: Pass this back to get more logs (pagination cursor, SSE only) - `complete`: true if job finished, false if more logs may be available - `total_logs`: total log entries before tail truncation REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs), timeout (default 50s, max 55s), last_event_id (for pagination), tail (return only last N entries) ⚠️ CONTEXT WARNING: Deploy logs can be hundreds of lines. Use tail: 50 for completed jobs to avoid blowing up the context window.

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• tflogs

  InsideOut (Riley)

  MONITORING: Fetch Terraform deployment logs with pagination Fetches logs from a running or completed Terraform deployment job. For **completed jobs**: uses REST endpoint for instant retrieval (supports `tail` for server-side filtering). For **running jobs**: streams via SSE with timeout-based pagination. **PAGINATION** (running jobs only): Use `last_event_id` from the response to fetch more: 1. First call: `tflogs(session_id='...')` → get logs + `last_event_id` 2. Next call: `tflogs(session_id='...', last_event_id='...')` → get NEW logs only 3. Repeat until `complete: true` in response **RESPONSE FIELDS**: - `logs`: Array of log messages collected - `last_event_id`: Pass this back to get more logs (pagination cursor, SSE only) - `complete`: true if job finished, false if more logs may be available - `total_logs`: total log entries before tail truncation REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs), timeout (default 50s, max 55s), last_event_id (for pagination), tail (return only last N entries) ⚠️ CONTEXT WARNING: Deploy logs can be hundreds of lines. Use tail: 50 for completed jobs to avoid blowing up the context window.

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• save_palette

  rnv-color-mcp

  Persist a named color palette for later retrieval with get_palette or list_palettes. colors is a list of hex values; optional notes are stored as the palette's description. Author is recorded as RNVizion. This WRITES to the palette store and is the only tool here that does. Reusing an existing name overwrites that palette: save and update are the same call (an upsert), there is no separate update operation. Returns a `durable` flag: true if the palette reached durable storage (the HF Dataset) and will survive a restart, false if it saved to the local working copy only (which is lost on rebuild, e.g. when the Space HF_TOKEN is missing or lacks write scope). Use when the user wants to keep a set of colors under a name for reuse across sessions, such as a brand or launch palette; to read a palette back use get_palette, and to see what already exists use list_palettes. The saved name can then be passed to mix_colors, convert_color, and generate_harmony as a palette reference.

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• get_access_pattern

  dynamical.org Weather & Climate Catalog

  Get the storage URI and working code for opening a dynamical.org dataset's data. dynamical.org publishes a Python package, `dynamical-catalog`, that reads the STAC catalog itself to resolve and open a dataset -- it's the recommended access pattern because it can't go stale even if the underlying storage format or location changes. This tool also returns the dataset's low-level storage details (from the STAC asset, fetched live) and a lower-level xarray/fsspec snippet for callers who need direct access instead of the wrapper package. Args: collection_id: A STAC collection id, e.g. "noaa-gfs-forecast". Use search_catalog to discover ids. Returns: A dict with the recommended `dynamical_catalog.open(...)` snippet, a `worked_example` pulled from the collection's own STAC metadata when one is published, the raw asset URI/type/storage options, and a generated low-level open snippet (icechunk/zarr/geoparquet, chosen from the asset's declared type). Raises ValueError (listing valid ids) if collection_id is unknown.

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• get_dataset_info

  dynamical.org Weather & Climate Catalog

  Get documentation, spatial/time resolution, domain, and update cadence for one dynamical.org dataset. dynamical.org/catalog is itself rendered from this same STAC catalog, so this tool fetches the collection document live (short TTL cache) rather than relying on anything baked into this server -- it's always as fresh as the STAC catalog itself. Args: collection_id: A STAC collection id, e.g. "noaa-gfs-forecast", "noaa-hrrr-analysis", or "ecmwf-aifs-ens-forecast". Use search_catalog to discover ids. Returns: A dict with title/model name, prose descriptions, spatial and time domain/resolution, forecast range (for forecast datasets), license and attribution, the dataset's variables, and links to its docs page and example notebooks. Raises ValueError (listing valid ids) if collection_id is unknown.

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• latest_deals

  deals

  The newest approved deals, freshest first — a pull-shaped view of the live deal stream. Returns up to 5 (max 10) compact deals with server-verified human_summary sentences. Editorial surface: availability-only price-target matches are excluded here (search_deals includes them). For ongoing monitoring, register_watch provides push delivery; always-on runtimes can consume the SSE river at https://api.kitsdeals.com/v1/river.

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• ic_research_ask

  Immersive Commons

  Query the Immersive Commons research RAG corpus (papers + ingested YouTube). Returns top-k chunks with similarity scores and source links. The query text is forwarded to a server-side RAG proxy (supercommons2 via Tailnet Funnel) and NEVER logged on the IC side — privacy contract. Use this for literature lookups, finding related work, surfacing citations the floor has already ingested. Args: { question: string (<=500 chars), k?: number (1-50, default 10), sources?: ('paper'|'book')[] (default ['paper']) }. Returns the upstream RAG response shape — typically { results: [{ paper_id, title, similarity, snippet, link }, ...] }. Required scope: research:query.

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• sti_get_platforms

  Stimulsoft Documentation MCP Server

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

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• resolve_topic

  Pine Script

  USE WHEN looking up an exact Pine Script API term or known concept keyword. Returns the best-matching doc paths with matched keywords and a retrieval suggestion (get_doc or list_sections + get_section). AFTER calling this tool, follow the suggestion: call get_doc() for small files or list_sections() + get_section() for large files. For natural language questions use search_docs() instead. Data sourced from bundled TOPIC_MAP and doc file content scan.

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• microsoft_docs_search

  xpay✦ DevTools Collection

  Search official Microsoft/Azure documentation to find the most relevant and trustworthy content for a user's query. This tool returns up to 10 high-quality content chunks (each max 500 tokens), extracted from Microsoft Learn and other official sources. Each result includes the article title, URL, and a self-contained content excerpt optimized for fast retrieval and reasoning. Always use this tool to quickly ground your answers in accurate, first-party Microsoft/Azure knowledge. ## Follow-up Pattern To ensure completeness, use microsoft_docs_fetch when high-value pages are identified by search. The fetch tool complements search by providing the full detail. This is a required step for comprehensive results.

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• dev_send

  Arcadia Finance

  DEV ONLY — Sign and broadcast an unsigned transaction using a local private key (PK env var). For production, use a dedicated wallet MCP server (Fireblocks, Safe, Turnkey, etc.) instead of this tool. Takes the transaction object returned by any write.* tool and submits it onchain.

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